Minimization for Signal and Image Recovery
L Huo, W Chen, H Ge, MK Ng - SIAM Journal on Imaging Sciences, 2023 - SIAM
The nonconvex optimization method has attracted increasing attention due to its excellent
ability of promoting sparsity in signal processing, image restoration, and machine learning …
ability of promoting sparsity in signal processing, image restoration, and machine learning …
Image restoration based on transformed total variation and deep image prior
L Huo, W Chen, H Ge - Applied Mathematical Modelling, 2024 - Elsevier
Most supervised learning methods require observation data and ground truth pairs as data
sets to train the network. However, it is difficult and time-consuming to obtain a large number …
sets to train the network. However, it is difficult and time-consuming to obtain a large number …
NeurTV: Total Variation on the Neural Domain
Recently, we have witnessed the success of total variation (TV) for many imaging
applications. However, traditional TV is defined on the original pixel domain, which limits its …
applications. However, traditional TV is defined on the original pixel domain, which limits its …
Fractional Fourier Transforms Meet Riesz Potentials and Image Processing
Via chirp functions from fractional Fourier transforms, we introduce fractional Riesz
potentials related to chirp functions, which are further used to give a new image encryption …
potentials related to chirp functions, which are further used to give a new image encryption …
Difference of anisotropic and isotropic TV for segmentation under blur and Poisson noise
In this paper, we aim to segment an image degraded by blur and Poisson noise. We adopt a
smoothing-and-thresholding (SaT) segmentation framework that finds a piecewise-smooth …
smoothing-and-thresholding (SaT) segmentation framework that finds a piecewise-smooth …
A stochastic ADMM algorithm for large-scale ptychography with weighted difference of anisotropic and isotropic total variation
Ptychography, a prevalent imaging technique in fields such as biology and optics, poses
substantial challenges in its reconstruction process, characterized by nonconvexity and …
substantial challenges in its reconstruction process, characterized by nonconvexity and …
[PDF][PDF] A new difference of anisotropic and isotropic total variation regularization method for image restoration
B Zhang, X Wang, Y Li, Z Zhu - Mathematical Biosciences and …, 2023 - aimspress.com
Total variation (TV) regularizer has diffusely emerged in image processing. In this paper, we
propose a new nonconvex total variation regularization method based on the generalized …
propose a new nonconvex total variation regularization method based on the generalized …
Superiorized iteration algorithm for CT image simultaneous reconstruction and segmentation
S Luo, Z Liu, Y Lu, XC Tai - Inverse Problems and Imaging, 2024 - aimsciences.org
We propose a model for computed tomography (CT) image reconstruction and segmentation
simultaneously, which can be applied to singleenergy spectral (traditional) CT (SECT) and …
simultaneously, which can be applied to singleenergy spectral (traditional) CT (SECT) and …
Enhanced total variation minimization for stable image reconstruction
The total variation (TV) regularization has phenomenally boosted various variational models
for image processing tasks. We propose to combine the backward diffusion process in the …
for image processing tasks. We propose to combine the backward diffusion process in the …
An Image Segmentation Model with Transformed Total Variation
Based on transformed $\ell_1 $ regularization, transformed total variation (TTV) has robust
image recovery that is competitive with other nonconvex total variation (TV) regularizers …
image recovery that is competitive with other nonconvex total variation (TV) regularizers …